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<p>This repository holds supplementary materials for Lyngs et al. (2019) "Self-Control in Cyberspace: Applying Dual Systems Theory to a Review of Digital Self-Control Tools".</p> <p>Paper abstract:</p> <p><em>Many people struggle to control their use of digital devices. However, our understanding of the design mechanisms that support user self-control remains limited. In this paper, we make two contributions to HCI research in this space: first, we analyse 367 apps and browser extensions from the Google Play, Chrome Web, and Apple App stores to identify common core design features and intervention strategies afforded by current tools for digital self-control. Second, we adapt and apply an integrative dual systems model of self-regulation as framework for organising and evaluating the design features found. Our analysis aims to help the design of better tools in two ways: (i) by identifying how, through a well-established model of self-regulation, current tools overlap and differ in how they support self-control; and (ii) by using the model to reveal underexplored cognitive mechanisms that could aid the design of new tools.</em></p> <p>In this repository, you will find: - The source file for the paper, <strong>main.Rmd</strong>, which lets you re-compile the paper and reproduce the plots and analyses (download the repository, then open the .Rproj file in RStudio, then open and knit <strong>main.Rmd</strong>) - The datasets reported in the paper (<strong>data/data_processed/</strong>) - Additional details on our process for reviewing and coding the design features in the apps and extensions (<strong>process_details/</strong>), as well as our raw coding data (<strong>data/data_raw/feature_coding/</strong>) - We encourage other researchers to re-use our data; re-run our analyses and inform us of any errors we may have made; use other inclusion criteria to select apps and extensions from the original search results (<strong>data/data_raw/search_data</strong>); etc.</p>
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